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Optical coherence tomography (OCT) is a high-resolution imaging technology probing the internal structure of multilayered tissues. Since it provides subsurface fingerprint information that is identical to the surface texture but unaffected by any surface defects, OCT-based fingerprints open up a new domain for establishing robust and high-security automatic fingerprint identification systems (AFISs). However, the development of OCT-based fingerprint recognition is hindered by the lack of public OCT-based fingerprint database for algorithm analysis and testing. This article, for the first time, established an OCT-based fingerprint database with thousands of fingers using our custom-built acquisition device. The website of this data set is https://github.com/CV-SZU/. Moreover, the images included in the database were selected after quality evaluation based on image resolution, image size, effective measured area, and the number of extractable features. Finally, case studies, including antispoofing, multiple subsurface fingerprint reconstruction, and fingerprint verification, were discussed based on the developed database. The database can serve as a benchmark for developing effective antispoofing, live detection, and high-accurate fingerprint recognition algorithms. It will significantly promote the research in the area of fingerprint biometric and will also advance the development of commercial products.
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Liu et al. (2020) studied this question.
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